JP2001117763A - Arithmetic unit for software scale, method for operating software scale and computer readable recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately estimate a software scale at the initial stage of system development. SOLUTION: Transactions of a prescribed unit to be executed by the system are distinguished by sorts such as external input EI, external output EO and external inquiry EQ and entities are distinguished by sorts such as internal logic file ILF and external interface file EIF by using keywords and entity names used for the description of a use case 101. Since a function point FP is calculated as a software scale value on the basis of the distinguished results, the software scale can be objectively estimated from the use case 101 resultant from defining a requested specification at the end stage of the definition of the requested specification.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to a software scale computing device for estimating software scale, a software scale computing method, and a computer-readable recording medium storing a program for realizing the software scale computing method.

[0002]

2. Description of the Related Art Generally, when a system is developed by software, it is coded through the steps of defining a required specification, basic design, detailed design, and the like, and is debugged as necessary to complete the system. In such a system development, it is important to estimate in advance the man-hours, the construction period, the construction cost, and the like of the development. To do so, it is necessary to understand the software scale of the system to be developed.

Conventionally, several techniques for estimating the scale of software have been proposed, one of which is called a function point method. The function point method divides processing and data performed by a system (software) to be developed into several types of classifications, and obtains the number of function points by multiplying weights determined for each classification. According to this method, compared to a method based on the number of lines of the source program,
Highly accurate estimation is possible.

[0004]

It is originally desirable that the above-mentioned estimation of the software scale be performed at an early stage of system development. However, in the conventional software scale estimating method, information necessary for the estimating is often not obtained until it reaches the stage of performing detailed design of the software. Therefore, when the above conventional method is used, the software scale can be actually grasped only after system development has progressed to some extent, and it is not possible to estimate the software scale in the initial stage of development. There is.

[0005] For this reason, in the past, in the early stage of the system development, it was a fact that a person estimated the software scale empirically and estimated the man-hour, the construction period, the cost, and the like of the system development. However, if a person empirically estimates the software size, the estimation result naturally differs depending on the person who estimates the software size. As a result, the software scale cannot be accurately determined,
There has been a problem that the man-hours, construction period, construction cost, and the like of system development cannot be clearly estimated.

The present invention has been made to solve such a problem, and an object of the present invention is to enable an accurate estimation of a software scale at an initial stage of system development without depending on human experience. And

[0007]

According to a first aspect of the present invention, there is provided a software-scale arithmetic unit, wherein the keyword and the entity name are selected from a use case in which at least a keyword and an entity name are described for a process performed by software. Extraction means for extracting the software, based on the keywords and entity names extracted by the extraction means, to which of a plurality of predetermined classifications each element necessary for calculating the scale of the software falls. And a calculation means for calculating a software scale value by performing an operation according to each classification on each of the elements based on the identification result by the classification identification means. Having.

According to a second aspect of the present invention, there is provided a software scale computing apparatus, wherein a process performed by software is divided into predetermined unit processes, and at least a keyword and an entity name are described for each of the predetermined unit processes. Extracting means for extracting the keyword and the entity name from the keyword, and based on the keyword and the entity name extracted by the extracting means, the predetermined unit process and the entity represented by the entity name are predetermined. Classification identification means for identifying which of the plurality of classifications corresponds to, and software processing by performing the predetermined unit processing and the operation for the entity according to each classification based on the identification result by the classification identification means. It is characterized by having an arithmetic means for calculating a value. A.

According to a third aspect of the present invention, in the second aspect of the present invention, the classification identifying means performs the predetermined unit processing based on a keyword extracted by the extracting means. It is characterized in that any of the above classifications is identified.

According to a fourth aspect of the present invention, in the second or third aspect of the invention, the classifying and identifying means determines the entity name based on a relationship between the keyword extracted by the extracting means and the entity name. Is characterized in that the entity represented by {circle around (1)} corresponds to one of a plurality of predetermined classifications.

According to a fifth aspect of the present invention, in the first to fourth aspects of the invention, the keyword is an external input which means a process to be performed by inputting data from the outside, and is performed by outputting data to the outside. The present invention is characterized in that it is a verb corresponding to each of an external output meaning a process and an external inquiry meaning a process performed by referring to data in software from outside.

According to a sixth aspect of the present invention, in the fifth aspect of the invention, the classification and identification means performs the predetermined unit processing based on the keyword extracted by the extraction means. The feature is that it identifies which classification of output or external inquiry.

According to a seventh aspect of the present invention, in the fifth and sixth aspects of the present invention, the classification identifying means determines the entity name based on a relationship between the keyword extracted by the extracting means and the entity name. Is characterized by the fact that the entity represented by is identified as an internal logical file that means that the data content can change internally, or an external interface file that only refers to external data. Having.

According to an eighth aspect of the present invention, in the first to seventh aspects, a use case creating means for describing a use case including at least the keyword and the entity name with respect to a process performed by software. It is characterized by having the following.

According to a ninth aspect of the present invention, in the first to eighth aspects, the extracting means extracts the entity name from the use case with reference to a data model defined for the entity. It is characterized by points.

The invention described in claim 10 is the invention according to claims 1 to 9
The invention described in (1) is characterized in that the use case is provided with an error check unit for checking an error whether information necessary for calculating the software scale value is appropriately described.

According to an eleventh aspect of the present invention, there is provided a method for calculating a software scale, comprising: extracting a keyword and an entity name from a use case in which at least a keyword and an entity name are described for a process performed by software; Based on the extracted keywords and entity names, a procedure for identifying each element required for calculating the scale of the software to which of a plurality of predetermined classifications, and a result of the identification On the basis of the above, the software scale value is calculated by performing an operation in accordance with each classification on each of the above elements.

According to a twelfth aspect of the present invention, there is provided a computer-readable recording medium, wherein a procedure for extracting the keyword and the entity name from a use case including at least a keyword and an entity name for a process performed by software. And a procedure for identifying which of the plurality of predetermined classifications each element required for calculating the scale of the software is based on the extracted keywords and entity names, Based on the result of (1), there is a feature in that a program for causing a computer to execute a procedure of calculating a software scale value by performing an operation according to each classification on each of the above-described elements is recorded.

According to the present invention described above, keywords and entity names are extracted from use cases created at an early stage of software development, and the scale of software is calculated based on the extracted information. Each of the necessary elements, for example, a predetermined unit process and an entity performed by software is identified as one of a plurality of predetermined classifications. Then, a software scale value is calculated by performing an operation corresponding to each classification based on the identification result.

[0020]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to FIGS. In the present embodiment, a description is made such that a predetermined keyword and an entity name are included in a use case that is a result of the definition of a required specification, and using this information, a software scale serving as an index indicating a software scale A function point is calculated as an example of a value.

FIG. 1 shows a block diagram of a software scale arithmetic unit for calculating function points. The use case creating unit 1 creates a use case 101 that is a result of the definition of the required specifications. A use case is a description of a series of events (actions) performed by an operator and a system during operation of the system in natural language, focusing on how the system to be developed is used in business. .

In the present embodiment, a series of events performed by the system are described so as to always include a keyword and an entity name described later for each predetermined processing unit. The predetermined processing unit is, for example, a minimum processing unit or a minimum function unit of the program, and is called these transactions. A plurality of use cases 101 are formed corresponding to various tasks of the system.

The data model creating section 2 creates a data model 102 which is a result of the definition of the required specifications. The data model is defined as various entities required for a system to be developed and relationships between the entities. Usually, data model 10
2 is created for one system. The transaction extracting unit 3 extracts a description of a process performed by the system from the use case 101 for each transaction.

The keyword / entity name extracting unit 4
For example, with reference to the data model 102 and the keyword definition information 103 prepared in advance, for each transaction extracted by the transaction extraction unit 3, a keyword and an entity name described later are extracted from the description. .

The transaction function classifying / identifying unit 5 divides each of the extracted transactions into any of a plurality of predetermined classes based on the keyword extracted for each transaction by the keyword / entity name extracting unit 4. Is to be identified. In addition, the data function classification identification unit 6
Is based on the association between the keyword and the entity name extracted for each transaction by the keyword / entity name extraction unit 4, to which of a plurality of predetermined classifications the entity represented by the entity name belongs. Is to be identified.

The FP calculation unit 7 performs a weighting operation according to each classification based on the results identified by the transaction function classification identification unit 5 and the data function classification identification unit 6 to obtain a function point indicating the software scale. FP is calculated. The error check unit 8 checks and displays an error as to whether the information necessary for calculating the function point FP is properly described in the description of the use case 101.

Hereinafter, each of the blocks 1 to 8 shown in FIG.
Before describing this in detail, the function point method used in the present embodiment will be briefly described.

In the present embodiment, the processing performed by the system to be developed is performed by an external input (E) for each transaction.
I: External Input), external output (EO: External Outpu)
t) and external inquiry (EQ: External Inquiry), and a transaction function point is obtained by adding an internationally determined weight to the number of transactions corresponding to each classification. The external input EI refers to a process performed by externally inputting data into the system.
O refers to processing performed by outputting data from the system to the outside, and external inquiry EQ refers to processing performed by externally referring to data in the system.

Each entity in the system to be developed is stored in an internal logic file (ILF: Internal Logic
al File), external interface file (EIF: Ext)
The data function points are obtained by classifying the data into two categories, namely, an ernal interface file, and adding an internationally determined weight to the number of entities corresponding to each category. The internal logical file ILF is data that is maintained and managed inside the system.
The external interface file EIF refers to data whose data content can be changed, and refers to data that is only referred to as external data and whose data content does not change.

The function point FP is calculated by adding the transaction function point and the data function point and multiplying the sum by an appropriate adjustment coefficient.

Hereinafter, each of the blocks 1 to 8 shown in FIG. 1 will be described in detail, and a process up to calculation of the function point FP will be described. FIG. 2 shows an outline up to the calculation of the function point FP in the present embodiment.

First, the use case 101 and the data model 102 created by the use case creating unit 1 and the data model creating unit 2 will be described. In the system development, a requirement specification is first defined, and the use case 101 and the data model 1 are defined as a result of the definition of the requirement specification.
02 is created.

FIG. 3 shows, as a specific example, a data model 102 created when a certain business system is developed.
FIG. 4 shows a use case 101 created for registering and editing an entity called a business process in the business system.

As shown in FIG. 3, in the data model 102, one or more entities required for the business system to be developed are defined in association with each other, and each entity is given an entity name.

In this example, each entity includes entities such as “business process”, “business system”, “internal actor”, “actor”, “external business process”, “internal business process”, and “valued service”. Name is given, name, ID, outline, importance,
Purposes are also defined. The lines connecting the entities represent associations, ● represents multiplicity, and Δ represents inheritance. As described above, as long as the data model 102 can express multiplicity and inheritance, various expressions such as a class diagram and an ER diagram can be used regardless of the form.

Further, as shown in FIG.
01, the title “Registration / editing of external business process” is first given. As the title, it is sufficient to roughly define the contents to be performed in the use case 101.

In the use case 101, generally, a precondition, a postcondition, and an event sequence (a basic sequence and an alternative sequence) are described following the title. Although not shown in FIG. 4, the precondition column describes conditions that need to be performed in advance to execute the use case 101. For example, the description is such that “the system is activated and the main menu is displayed”. Also,
The post-condition field describes what the state will be after the event series of the use case 101 is performed.

Normally, an event sequence, which is the core of the use case 101, is subsequently described. In the use case 101 shown in FIG. A list is described, and tags S1 to S7 are attached to each function. These functions define processing performed by the system that is the smallest as viewed from the user side as one unit, and each function corresponds to the above-described transaction.

The event series is described in the column (2). As described above, a series of events (actions) performed by the actor and the system are described in the natural language in the event series column. , The interaction between the actor and the system is described in order. Here, only the basic sequence is shown as a representative example.

An event performed by an actor is described after adding an A tag. The description of the event performed by the actor may be freely described without any limitation.

On the other hand, regarding the processing performed by the system,
Describe in units of one transaction. In addition to simply adding a tag of S to each transaction, tags S1 to S7 used in the function list in the above column (1) are added so as to correspond to the function.

In this case, if the function list of the above column (1) is described in the use case 101, the tags S1 to S7 can be correctly attached by comparing with the function list. However, the column (1) is not essential and need not be described in the use case 101. In the use case 101 shown in FIG. 4, the tags S1 to S7 appear only once, but the same tag S1 to S7 may appear a plurality of times if there is processing of the same function.

Further, when describing the processing performed by the system, the entity name defined in the data model 102 related to the transaction is specified, and the entity name is enclosed in []. And
Using a verb defined in advance as a keyword, the entity is described while clarifying which function is described in the function list in the above column (1) and how the entity is related.

The verb serving as the keyword is defined as follows. That is, in the present embodiment, in order to calculate the function point FP, the processing performed by the system includes an external input EI, an external output EO, and an external inquiry EQ.
Which of the three classifications is applicable is identified. Therefore, for each of the external input EI, external output EO, and external inquiry EQ, a verb meaning a corresponding process is defined as a keyword.

The external input EI is, as described above, a process performed by externally inputting data into the system. Therefore, verbs such as “add”, “update”, and “delete” corresponding to the process are defined as keywords representing the external input EI. When describing the event series of the use case 101, be sure to specify the entity name enclosed in [] and add it to [Entity name]. Update [Entity name]. Delete [Entity name]. It is described as follows. In use case 101 shown in FIG.
For example, "S3: [External business process] is added,
Return to step 2. There is a description. It can be seen that such a description includes an entity name of an external business process and a keyword representing the external input EI.

The external output EO refers to a process of outputting data from the system to the outside as described above. Therefore, as a keyword representing the external output EO, “print”, “output”,
Verbs such as "deriving" are defined as keywords. Then, when describing the event series, ~ is printed on /. Is output to /. Is derived. It is described as follows.

"Deriving" is used when performing operations such as calculating and counting.
Used in conjunction with the verbs "print", "output", and "display". For example, "the total sales amount from April to March of the following year is derived and displayed on the screen." In use case 101 shown in FIG. 4, a verb corresponding to external output EO is not used.

As described above, the external inquiry EQ refers to a process performed by externally referring to data in the system. Therefore, as a keyword representing the external inquiry EQ,
"Refer to (list) and display" corresponding to the process,
Verbs such as "refer to (list) and print" are defined as keywords. When describing the event series, be sure to specify the entity name enclosed in [] and refer to [list of entities] and display (list).
Refer to [Entity name] and print (list). It is described as follows.

When a search result is displayed (listed) by referring to the database at the time of screen display, the description is always made using a keyword such as "refer to and display" as described above. It shall be. For a mere screen display without reference to a database, a description such as “display a screen” is made as usual. In the use case 101 shown in FIG. 4, for example, there is a description that "S1: The system displays an external business process list screen with reference to [external business process]." It can be seen that such a description includes an entity name of an external business process and a keyword representing an external inquiry EQ.

Returning to FIG. 1, the transaction extracting section 3 extracts a description of the processing performed by the system from the event series of the use case 101 created as described above for each transaction. In this case, the tags S1 to S
7, the transaction can be easily cut out by detecting these tags S1 to S7.

The keyword / entity name extracting unit 4 extracts a keyword and an entity name for each transaction from the description of the processing performed by the system extracted for each transaction by the transaction extracting unit 1. As shown in FIG. 1, the keyword can be extracted by comparing it with a keyword definition 103 indicating what keyword is defined. The extraction of the entity name can be easily performed by detecting the [] because the entity name is enclosed in [] in the description of the processing performed by the system.

Note that the entity name can be extracted even if the entity name is not enclosed in []. In this case, as shown in FIG.
(Alternatively, a list of entity names may be used instead of the data model 102 itself), and it is determined whether the description of the processing performed by the system includes the entity name defined by the data model 102. Then, if it exists, its entity name may be extracted.

The transaction function classifying / identifying unit 5 classifies each of the extracted transactions based on the keyword extracted by the keyword / entity name extracting unit 2 into any one of the external input EI, external output EO, and external inquiry EQ. Identify if

That is, as shown in FIG. 2, if there is a keyword such as “add”, “update”, or “delete” in the description of the transaction regarding the processing performed by the system, the transaction is stored in the external input EI. Classify and count. In the example of the use case 101 shown in FIG. 4, transactions tagged with S3, S5, and S6 are counted as the external input EI.

Further, the description of the transaction regarding the processing performed by the system includes “print”, “output”,
If there is a keyword such as "deriving", the transaction is classified into the external output EO and counted. In the example of use case 101 shown in FIG. 4, none of the transactions is counted as the external output EO.

If there is a keyword such as “reference (list) display” or “reference (list) print” in the description of the transaction regarding the processing performed by the system, the transaction is included in the external inquiry EQ. Classify and count. In the example of the use case 101 shown in FIG. 4, transactions tagged with S1, S2, S4, and S7 are counted as the external inquiry EQ.

As described above, for all the created use cases 101, the external input EI, the external output EO, and the external inquiry EQ are classified based on the keyword for each transaction performed by the system included therein. Identify and count. At this time, if the same process is duplicated for the same entity name,
Do not count duplicately. Regardless of whether the same function process is performed once or multiple times for an entity,
This is because the software scale of the system to be developed does not change.

On the other hand, the data function classification identification section 6
Then, based on the relationship between the keyword extracted by the keyword / entity name extracting unit 2 and the entity name, the entity represented by the entity name falls into any of the classification of the internal logical file ILF and the external interface file EIF. Identify. That is, whether the entity represented by the extracted entity name merely refers to the data corresponding to the entity name or may be updated is determined from the keyword associated with the entity name. .

Specifically, all use cases 101
If the entity represented by the extracted entity name has been updated at least once, that is, if the keyword of the external input EI is associated with the entity name even once and described, ,
The entity is classified into the internal logical file ILF and counted.

The entity represented by the extracted entity name has never been updated.
That is, if the keyword of the external input EI has never been associated and described in the use case 101, the entity is stored in the external interface file EIF.
Classify and count.

As shown in FIG. 2, the FP calculation unit 7 assigns a predetermined weight to the number of transactions counted for each of the external input EI, external output EO, and external inquiry EQ by the transaction function classification identifying unit 5, The external input EI is x4, the external output EO is x5, and the external inquiry EQ is x4, and a transaction function point is calculated. In addition, the number of entities counted for each classification of the internal logical file ILF and the external interface file EIF by the data function classification identifying unit 6 is given a predetermined weight, the internal logical file ILF is × 10, and the external interface file EIF is
Perform x7 to calculate the data function point.

Then, by adding these transaction function points and data function points and multiplying them by a predetermined adjustment coefficient,
Calculate function point FP. When the function point FP is calculated in this way, the man-hour, the work period, the work cost, and the like of the system development can be estimated based on the value.

FIG. 5 shows a function point FP
An example of the flow up to the calculation is shown in a flowchart. First, in step P10, a description of the processing performed by the system is cut out from the event series of the use case 101 for each transaction. Next, in step P11, a keyword and an entity name are extracted for each transaction from the description of the processing performed by the system extracted for each transaction.

Then, in step P12, based on the extracted keywords, each of the transactions extracted for the processing performed by the system is input to the external input E.
I, the external output EO, and the external inquiry EQ are classified and counted. In step P13,
For all the created use cases 101, it is determined whether the classification of the external input EI, the external output EO, and the external inquiry EQ is identified and counted.

If it is determined in step P13 that there is a use case 101 whose classification has not been identified, the process returns to step P10, and the above processing is repeated until all the use cases 101 have been processed. On the other hand, when it is determined in step P13 that the classification of all the use cases 101 has been completed, the process proceeds to step P14, and based on the association between the keyword and the entity name extracted in step P11, The entity represented by the entity name is an internal logical file ILF,
The classification of the external interface file EIF is identified and counted.

Next, at step P15, the external input E
A predetermined weight (× 4, × 4) is assigned to the number of transactions classified as I, external output EO, and external inquiry EQ, respectively.
5 × 4) to perform the transaction function
Calculate points. Also, the internal logical file ILF,
A predetermined weight is assigned to the number of entities classified in the external interface file EIF (× 10, × 7)
To calculate the data function point.
Then, the transaction function point and the data function point are added and multiplied by a predetermined adjustment coefficient to calculate a function point FP.

The error checking unit 8 shown in FIG. 1 checks for errors in the description of the use case 101. The following checking methods are conceivable. For example, when a verb other than a keyword is used in the description of the processing performed by the system in the event series of the use case 101, the verb may be listed up and notified to the user.

Alternatively, the entity name of the entity defined in the data model 102 is compared with the entity name extracted by the keyword / entity name extracting unit 4 to determine the keyword entity If there is an entity name that has not been extracted by the name extracting unit 4, the unused entity name may be listed up and notified to the user.

Alternatively, if the same tag S1 to S7 is added to the description of the processing performed by the system cut out for each transaction, but a verb of a different keyword is used, the verb is listed. The user may be notified. In other words, each of the cut-out transactions should be classified into any one of the external input EI, the external output EO, and the external inquiry EQ.
This is because the verb serving as the keyword is considered to have been used incorrectly.

As described above, according to the present embodiment, the use case 101 which is the result of the definition of the required specification is described so as to include the keyword and the entity name, and the keyword and the entity extracted from the use case 101 are described. Function point F using entity name
Since the elements necessary for P calculation were classified,
At the initial stage of system development when the definition of requirements specifications has been completed,
It is possible to obtain the minimum information required for the calculation and calculate the function point FP. And
If the function point FP can be calculated, man-hours, work period, work cost, and the like of the system development can be estimated at an early stage of the system development.

Further, at the initial stage of system development, the software scale can be estimated based on objective numerical values of function points FP calculated by a predetermined operation instead of based on human experience. There is no difference in the result, and it is possible to more accurately estimate the man-hour, the construction period, the construction cost, and the like of the system development. Also, once the software scale is estimated, the use case 101 and the data model 102 are modified to match the planned software scale,
It is also possible to appropriately change the system development policy at the stage of defining the required specifications.

Furthermore, since the use case 101 is described using keywords, there is an advantage that the quality of the use case 101 can be maintained constant regardless of the person who writes the use case.

In the above embodiment, the external input EI,
External output EO, external query EQ, internal logical file IL
F, the function points FP are calculated by a simple method of weighting each element such as the external interface file EIF with a fixed weight. For example, a predetermined item included in each entity at the stage of defining required specifications If the number is known, the function point FP may be calculated by changing the weight according to the complexity of each element according to the number of items.

In the above embodiment, the external input EI,
External output EO, external query EQ, internal logical file IL
F, the external interface file EIF is an element necessary for calculating the function point FP. However, in addition to these or at least a part of them, other elements may be used as elements. For example, the function point FP may be calculated using the form, the number of screens, and the like as elements.

The embodiment described above is constituted by a computer CPU or MPU, RAM, ROM, etc., and can be realized by operating a program recorded in the RAM or ROM. Therefore, the present invention can be realized by recording a program that causes a computer to perform the above function on a recording medium and causing the computer to read the program. As a recording medium,
CD-ROM, floppy disk, hard disk,
A magnetic tape, a magneto-optical tape, a nonvolatile memory card, or the like can be used.

The functions of the above-described embodiments are realized when the computer executes the supplied program, and the program code is executed by an OS (Operating System) or other application software running on the computer. Needless to say, the program code is also included in the embodiment of the present invention when the functions of the above-described embodiment are realized in cooperation with the above.

Note that each of the above embodiments is merely a specific example for carrying out the present invention, and the technical scope of the present invention should not be interpreted in a limited manner. That is, the present invention can be implemented in various forms without departing from the spirit or main features thereof.

[0078]

As described above, according to the present invention, the elements required for calculating the software scale value using the keywords and the entity names included in the use cases which are the result of the definition of the required specifications. Is classified, so that the software scale value can be calculated in the initial stage of system development in which the definition of the required specifications has been completed. Therefore, it is possible to estimate the software scale at the initial stage of system development, and to estimate the man-hours, construction period, cost, and the like of system development. Moreover, in the early stage of system development,
The software scale can be estimated based on an objective numerical value called the software scale value instead of based on human experience, so that there is no difference in the result depending on the person, and the man-hour and time required for system development can be more accurately determined , Construction costs, etc. can be estimated.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a software scale operation device according to an embodiment of the present invention.

FIG. 2 is a diagram showing an outline up to calculation of a function point FP.

FIG. 3 is a diagram showing a specific example of a data model 102;

FIG. 4 is a diagram showing a specific example of a use case 101.

FIG. 5 is a flowchart showing an example of a flow up to calculation of a function point FP.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Use case creation part 2 Data model creation part 3 Transaction extraction part 4 Keyword / entity name extraction part 5 Transaction function classification identification part 6 Data function classification identification part 7 FP calculation part 101 Use case 102 Data model 103 Keyword definition information

Continued on the front page (72) Inventor Yu Sakaguchi 2-6-3 Otemachi, Chiyoda-ku, Tokyo Inside Nippon Steel Corporation (72) Inventor Nobuo Takayanagi 2-6-3 Otemachi, Chiyoda-ku, Tokyo New Japan F-term (reference) in Iron Corporation 5B076 DD02 EC02 EC10

Claims (12)

[Claims] 1. An extracting means for extracting a keyword and an entity name from a use case in which at least a keyword and an entity name are described with respect to a process performed by software, and a keyword and an entity name extracted by the extracting means. Based on the identification result of each of the elements required for calculating the scale of the software based on the classification identification means for identifying which of a plurality of predetermined classifications corresponds to, based on the identification result by the classification identification means, A calculating means for calculating a software scale value by performing an arithmetic operation on each of the elements according to each classification. 2. An extracting means for dividing a process performed by software into predetermined unit processes, and extracting the keyword and the entity name from a use case described including at least a keyword and an entity name for each predetermined unit process. A classification for identifying which of the plurality of predetermined classifications each of the entity represented by the predetermined unit processing and the entity name is based on the keyword and the entity name extracted by the extraction means; Identification means; and operation means for calculating a software scale value by performing an operation according to each classification on the predetermined unit processing and the entity based on an identification result by the classification identification means. Software scale computing device. 3. The classification identifying means identifies which of the plurality of predetermined classifications the predetermined unit process corresponds to, based on the keyword extracted by the extracting means. The software scale operation device according to claim 2. 4. The classification identifying means, based on a relationship between the keyword extracted by the extracting means and an entity name, determines whether an entity represented by the entity name falls into any of a plurality of predetermined classifications. 4. The software-scale arithmetic device according to claim 2, wherein whether to perform the operation is identified. 5. The keyword is an external input which means a process to be performed by inputting data from the outside, an external output which means a process to be performed by outputting data to the outside, and a data to be performed by referring to data in software from outside. The software scale operation device according to any one of claims 1 to 4, wherein the device is a verb corresponding to each of the external queries that mean a process. 6. The classification identifying means identifies which of the external input, external output, and external inquiry the predetermined unit processing corresponds to, based on the keyword extracted by the extracting means. The software scale operation device according to claim 5, wherein: 7. The classifying means means that the entity represented by the entity name can change data content internally based on the relationship between the keyword extracted by the extracting means and the entity name. 7. The method according to claim 5, wherein the classification is performed to identify which of the internal logical file and the external interface file which means only those referred to as external data.
Software scale arithmetic unit according to 1. 8. The processing performed by the software,
8. The software scale operation device according to claim 1, further comprising use case creation means for describing a use case including at least the keyword and the entity name. 9. The method according to claim 1, wherein the extracting unit extracts the entity name from the use case with reference to a data model defined for the entity. Software scale arithmetic unit. 10. An apparatus according to claim 1, further comprising an error check unit for checking an error as to whether information necessary for calculating said software scale value is properly described for said use case. Any one of
Software scale arithmetic unit according to the paragraph. 11. A procedure for extracting the keyword and the entity name from a use case in which at least a keyword and an entity name are described with respect to a process performed by the software, and based on the extracted keyword and the entity name, A procedure for identifying which of the plurality of predetermined classifications each element required for calculating the scale of software corresponds to, and a classification for each of the above elements based on the result of the above identification. Calculating a software scale value by performing a corresponding calculation. 12. A procedure for extracting the keyword and the entity name from a use case in which at least a keyword and an entity name are described with respect to a process performed by the software; and A procedure for identifying which of the plurality of predetermined classes each element required for calculating the scale of the software corresponds to, and a classification for each of the above elements based on the result of the above identification. A computer-readable recording medium which stores a program for causing a computer to execute a procedure for calculating a software scale value by performing a corresponding operation.